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BEGIN:VEVENT
DTSTAMP:20250522T212947Z
LOCATION:Mile High 4
DTSTART;TZID=America/Denver:20240729T140000
DTEND;TZID=America/Denver:20240729T141000
UID:siggraph_SIGGRAPH 2024_sess106_papers_183@linklings.com
SUMMARY:Conditional Mixture Path Guiding for Differentiable Rendering
DESCRIPTION:Zhimin Fan (Nanjing University); Pengcheng Shi (State Key Lab 
 for Novel Software Technology, Nanjing University); and Mufan Guo, Ruoyu F
 u, Yanwen Guo, and Jie Guo (Nanjing University)\n\nThis work develops a pa
 th guiding based on a distribution mixture that improves the performance o
 f differentiable rendering processes. It demonstrates why the mixture is r
 equired, how to obtain this distribution mixture, how to update each distr
 ibution at each iteration, and how to handle negative gradients.\n\nIntere
 st Area: Research & Education\n\nRecording: Livestreamed, Recorded\n\nKeyw
 ord: Machine Learning, Rendering\n\nRegistration Category: Full Conference
 , Full Conference Supporter, Virtual Access, Exhibitor Full Conference, Mo
 nday\n\nSession Chair: Ioannis Gkioulekas (Carnegie Mellon University)\n\n
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